/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU General Public License as published by
 *   the Free Software Foundation, either version 3 of the License, or
 *   (at your option) any later version.
 *
 *   This program is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

/*
 * DiscreteEstimatorFullBayes.java
 * Copyright (C) 2012 University of Waikato, Hamilton, New Zealand
 * 
 */
package weka.classifiers.bayes.net.estimate;

import weka.estimators.DiscreteEstimator;

/**
 * Symbolic probability estimator based on symbol counts and a prior.
 * 
 * @author Remco Bouckaert (rrb@xm.co.nz)
 * @version $Revision$
 */
public class DiscreteEstimatorFullBayes extends DiscreteEstimatorBayes {

    /** for serialization */
    static final long serialVersionUID = 6774941981423312133L;

    /**
     * Constructor
     * 
     * @param nSymbols  the number of possible symbols (remember to include 0)
     * @param w1
     * @param w2
     * @param EmptyDist
     * @param ClassDist
     * @param fPrior
     */
    public DiscreteEstimatorFullBayes(int nSymbols, double w1, double w2, DiscreteEstimatorBayes EmptyDist, DiscreteEstimatorBayes ClassDist, double fPrior) {

        super(nSymbols, fPrior);

        m_SumOfCounts = 0.0;
        for (int iSymbol = 0; iSymbol < m_nSymbols; iSymbol++) {
            double p1 = EmptyDist.getProbability(iSymbol);
            double p2 = ClassDist.getProbability(iSymbol);
            m_Counts[iSymbol] = w1 * p1 + w2 * p2;
            m_SumOfCounts += m_Counts[iSymbol];
        }
    } // DiscreteEstimatorFullBayes

    /**
     * Main method for testing this class.
     * 
     * @param argv should contain a sequence of integers which will be treated as
     *             symbolic.
     */
    public static void main(String[] argv) {
        try {
            if (argv.length == 0) {
                System.out.println("Please specify a set of instances.");

                return;
            }

            int current = Integer.parseInt(argv[0]);
            int max = current;

            for (int i = 1; i < argv.length; i++) {
                current = Integer.parseInt(argv[i]);

                if (current > max) {
                    max = current;
                }
            }

            DiscreteEstimator newEst = new DiscreteEstimator(max + 1, true);

            for (int i = 0; i < argv.length; i++) {
                current = Integer.parseInt(argv[i]);

                System.out.println(newEst);
                System.out.println("Prediction for " + current + " = " + newEst.getProbability(current));
                newEst.addValue(current, 1);
            }
        } catch (Exception e) {
            System.out.println(e.getMessage());
        }
    } // main

} // class DiscreteEstimatorFullBayes
